Ntoumanis N., Myers N.D. An Introduction to Intermediate and Advanced Statistical Analyses for Sport and Exercise Scientists

New York: John Wiley & Sons, 2016. — 315 p."Ntoumanis and Myers have done sport and exercise science researchers and students a tremendous service in producing An Introduction to Intermediate and Advanced Statistical Analyses for Sport and Exercise Scientists. This book has an outstanding compilation of comprehensible chapters dealing with the important concepts and technical minutia of the statistical analyses that sport and exercise science scholars use (or should be using!) in their efforts to conduct meaningful research in the field. It is a resource that all sport and exercise scientists and their students should have on their book shelves." --Robert Eklund, School of Sport, University of Stirling, UK "Motivating, to have a statistics text devoted to enabling researchers studying sport and exercise science to apply the most sophisticated analytical techniques to their data. Authors hit the mark between using technical language as necessary and user-friendly terms or translations to keep users encouraged. Text covers traditional and well-used tools but also less common and more complex tools, but always with familiar examples to make their explanations come alive. As a dynamic systems theorist and developmentalist, I would love to see more researchers in my area create study designs that would enable the use of tools outlined here, such as multilevel structural equation modeling (MSEM) or mediation & moderation analyses, to uncover cascades of relations among subsystems contributing to motor performance, over time. This text can facilitate that outcome." --Beverly D. Ulrich, School of Kinesiology, University of Michigan, USA "The domain of quantitative methods is constantly evolving and expanding. This means that there is tremendous pressure on researchers to stay current, both in terms of best practices and improvements in more traditional methods as well as increasingly complex new methods. With this volume Ntoumanis and Myers present a nice cross-section of both, helping sport and exercise science researchers to address old questions in better ways, and, even more excitingly, to address new questions entirely. I have no doubt that this volume will quickly become a lovingly dog-eared companion for students and researchers, helping them to continue to move the field forward." --Gregory R. Hancock, University of Maryland and Center for Integrated Latent Variable Research (CILVR), USATitle Page
Copyright PageAbout the editors
List of contributors
ForewordFactorial ANOVA and MANOVA
General Introduction
Hypothesis Testing
Alpha Level
Assumptions
Further Considerations
Utility in Sport and Exercise Sciences
Treatment Conditions
Existing Conditions
Individual Characteristics
Recent Usage
The Substantive Example
Univariate: Factorial ANOVA
Univariate Assumptions
The Synergy
Factorial ANOVA Analysis Plan
Example of a Write-Up Compatible with the APA Publication Manual
Factorial MANOVA Analysis Plan
Example of a Write-Up Compatible with the APA Publication ManualRepeated measures ANOVA and MANOVA
General Introduction
Between- versus Within-Subjects Variables
Hypothesis Testing
Assumptions
Further Considerations
Utility in Sport and Exercise Sciences
Multiple Treatment Conditions
Multiple Assessments
Longitudinal Studies
Recent Usage
The Substantive Example
Univariate: Repeated Measures ANOVA
Univariate Assumptions
Multivariate: Repeated Measures MANOVA
Multivariate Assumptions
The Synergy
Repeated Measures ANOVA Analysis Plan
Example of a Write-Up Compatible with the APA Publication Manual
Repeated Measures MANOVA Analysis Plan
Example of a Write-Up Compatible with the APA Publication ManualMediation and moderation via regression analysis
General Introduction
Utility of the Methods in Sport and Exercise Science
The Substantive Example
Mediation
The Synergy
Mediation
The Substantive Example
Moderation
The Synergy
ModerationChapter 4 Item response theory and its applications in Kinesiology
General Introduction
What Is IRT?
Other Commonly Used IRT Models
Assumptions Related to IRT
Unidimensionality
Local Independence
Addressing Model-Data Fit
Inspecting Model Assumptions
Inspecting Expected Model Features
Inspecting Overall Model-Data Fit
Computer Simulation for Model-Data Fit Testing
Unique Features and Advantages of IRT
Estimation Invariance
Common Metric Scale
Item and Test Information
Test Relative Efficiency
Global “Reliability” Is no Longer a Concern
Item Bank and IRT-Based Test Construction
Parameter Estimation and Software
Utility of the Methodology in Kinesiology
IRT Limitations and Future DirectionIntroduction to factor analysis and structural equation modeling
General Introduction
Utility of the Method in Sport and Exercise Science
Terminology and Methodology
Evaluating Model Fit
Interpreting Parameter Estimates
The Substantive Example
The Synergy
EFA: Establishing the Factor Structure
CFA: Testing the Measurement Models
Structural Equation Modeling: Adding the Regression PathsInvariance testing across samples and time: Cohort-sequence analysis of perceived body composition
General Introduction to the Importance of Measurement Invariance
Cohort-Sequential Designs: Longitudinal Invariance across Samples and Time
Substantive Application: Physical Self-Concept
Methodology
The PSDQ Instrument
Statistical Analyses
Goodness of Fit
Results
Basic Cohort-Sequence Model: Four Cohort Groups and Four Waves
Cohort-Sequence Design of Multiple Indicators, Multiple Causes Models
Use of Model Constraint with Orthogonal Polynomial Contrasts to Evaluate Cohort Sequence and MIMIC Latent Means
Use of Latent Growth Curve Models to Evaluate Stability/Change over Time
LGC Results
Summary, Implications, and Further Directions
Methodological Implications, Limitations, and Further DirectionsCross-lagged structural equation modeling and latent growth modeling
General Introduction
A Theoretical Framework for the Study of Change
Utility of the Method in Sport and Exercise Science
Analysis of Change
The Substantive Example
Theoretical Background
The Data: Participants and Measurement
The Synergy
CLPM
CLPM Example
Latent Growth Modeling
LGM Example
Model 2a: Unconditional LGM
Model 2b: Conditional LGM
Model 2c: Unconditional LGM with TVCs
Model 3: Parallel Process LGM
Model 4: Second-Order LGMExploratory structural equation modeling and Bayesian estimation
General Introduction
Utility of the Methods in Sport and Exercise Science
The Substantive Example(s)
The Motivational Correlates of Mentally Tough Behavior
Developing Synergies through Statistical Modeling
ESEM
Bayesian EstimationA gentle introduction to mixture modeling using physical fitness performance data
General Introduction
Utility of the Method in Sport and Exercise Science
The Substantive Example(s)
Class Enumeration in Mixture Models
The Estimation of Mixture Models
The Synergy
LPA of Grade 5 Students and Tests of Invariance across Gender Groups
Inclusion of Covariates in LPA Solutions
LTA
Mixture Regression Analyses of Grade 5 Students
Latent Basis Growth Mixture Analyses: Cardiovascular Fitness
Piecewise Growth Mixture Analyses: Physical StrengthMultilevel (structural equation) modeling
General Introduction
Multilevel Structural Equation Modeling
Utility of the Methodology in Sport and Exercise Science
The Substantive Examples
Coaching Competency–Collective Efficacy–Team Performance: 1–1–2
Action Planning Intervention–Physical Activity Action Plans–Physical Activity: 2–1–1
The Synergy
Coaching Competency–Collective Efficacy–Team Performance: 1–1–2
Action Planning Intervention–Physical Activity Action Plans–Physical Activity: 2–1–1Application of meta-analysis in sport and exercise science
General Introduction
Stages of Meta-Analysis
Key Elements of Meta-Analysis
Goals of Meta-Analysis
Utility of the Methodology in Sport and Exercise Science
The Substantive Example
The Synergy
Univariate Meta-Analysis
Multivariate Meta-AnalysisReliability and stability of variables/instruments used in sport science and sport medicineA. Assessment of Test–Retest Agreement Using Interval/Ratio Data
A Worked Example Using the Test–Retest Differences of the Biceps Skinfold Measurements
B. Utility of the Assessment of Test-Retest Stability Using Categorical/Likert-Type Data
The Substantive Example
Utility of the Test–Retest Stability Using Nonparametric Data
The Synergy
Utility of the Item by Item Approach to Test–Retest Stability
The SynergySample size determination and power estimation in structural equation modeling
General Introduction
Power
Power Analysis in SEM
Utility of the Methodology in Sport and Exercise Science
Power Analysis Regarding Model-Data Fit: An Introduction
Power Analysis Regarding Focal Parameters: An Introduction
The Substantive Example
Bifactor Model in Sport and Exercise Science
Bifactor Model and the PETES
The Synergy
Power Analysis Regarding Model-Data Fit: A Demonstration
Power Analysis Regarding Focal Parameters: A DemonstrationEULA